You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
CDG: An Online Server for Detecting Biologically Closest Disease-Causing Genes and its Application to Primary Immunodeficiency
|
|---|---|
| Published in |
Frontiers in immunology, June 2018
|
| DOI | 10.3389/fimmu.2018.01340 |
| Pubmed ID | |
| Authors |
David Requena, Patrick Maffucci, Benedetta Bigio, Lei Shang, Avinash Abhyankar, Bertrand Boisson, Peter D. Stenson, David N. Cooper, Charlotte Cunningham-Rundles, Jean-Laurent Casanova, Laurent Abel, Yuval Itan |
| Abstract |
High-throughput genomic technologies yield about 20,000 variants in the protein-coding exome of each individual. A commonly used approach to select candidate disease-causing variants is to test whether the associated gene has been previously reported to be disease-causing. In the absence of known disease-causing genes, it can be challenging to associate candidate genes with specific genetic diseases. To facilitate the discovery of novel gene-disease associations, we determined the putative biologically closest known genes and their associated diseases for 13,005 human genes not currently reported to be disease-associated. We used these data to construct the closest disease-causing genes (CDG) server, which can be used to infer the closest genes with an associated disease for a user-defined list of genes or diseases. We demonstrate the utility of the CDG server in five immunodeficiency patient exomes across different diseases and modes of inheritance, where CDG dramatically reduced the number of candidate genes to be evaluated. This resource will be a considerable asset for ascertaining the potential relevance of genetic variants found in patient exomes to specific diseases of interest. The CDG database and online server are freely available to non-commercial users at: http://lab.rockefeller.edu/casanova/CDG. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| France | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 20% |
| Student > Bachelor | 3 | 15% |
| Student > Ph. D. Student | 3 | 15% |
| Other | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 3 | 15% |
| Unknown | 3 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 25% |
| Medicine and Dentistry | 5 | 25% |
| Computer Science | 4 | 20% |
| Immunology and Microbiology | 2 | 10% |
| Business, Management and Accounting | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 3 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2019.
All research outputs
#16,053,755
of 25,385,509 outputs
Outputs from Frontiers in immunology
#16,721
of 31,537 outputs
Outputs of similar age
#198,842
of 342,755 outputs
Outputs of similar age from Frontiers in immunology
#457
of 727 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,537 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 342,755 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 727 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.